Physics-informed digital twin and onboard control of a brainbot for intelligent active matter

Mammadli I, Shrestha P, Pande J, Novkoski F, Mohapatra S, Noirhomme M, Maier A, Smith AS, Vandewalle N (2026)

Publication Language: English

Publication Type: Journal article, Original article

Publication year: 2026

Journal

Book Volume: 8

Pages Range: 033164

Journal Issue: 3

URI: https://link.aps.org/doi/10.1103/rd1t-h2v6

DOI: 10.1103/rd1t-h2v6

Open Access Link: https://doi.org/10.1103/rd1t-h2v6

Abstract

Establishing adaptive particles that sense their state, anticipate their evolution, and compute control inputs onboard has been a major challenge in nonequilibrium physics. We address this challenge by realizing an autonomous brainbot, building on a recently developed programmable bristlebot. First, we construct a physics-informed digital twin of the device, based on a kinematic model that reproduces measured trajectory statistics and generates long, statistically faithful synthetic trajectories. The kinematics forms the foundation for implementing onboard model predictive control, enabling autonomous trajectory tracking, demonstrated by accurate execution of a nontrivial target path. This provides a proof of principle for a brainbot that senses its state, predicts its evolution, and computes control inputs onboard, unlike conventional active particles with fixed motility, thereby transforming the brainbot into an agentic physical entity. By integrating physical modeling, data-driven parameter identification, and control into a unified framework, our approach provides a scalable platform for machine-learning-enabled multiagent studies and lays the groundwork for intelligent, adaptive active matter.

Authors with CRIS profile

Involved external institutions

University of Liège (ULg) / Université de Liège Belgium (BE) FLAME University India (IN)

How to cite

APA:

Mammadli, I., Shrestha, P., Pande, J., Novkoski, F., Mohapatra, S., Noirhomme, M.,... Vandewalle, N. (2026). Physics-informed digital twin and onboard control of a brainbot for intelligent active matter. Physical Review Research, 8(3), 033164. https://doi.org/10.1103/rd1t-h2v6

MLA:

Mammadli, Isa, et al. "Physics-informed digital twin and onboard control of a brainbot for intelligent active matter." Physical Review Research 8.3 (2026): 033164.

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